CN111991013A - Skeletal muscle strength and human body stability detection system and detection method thereof - Google Patents
Skeletal muscle strength and human body stability detection system and detection method thereof Download PDFInfo
- Publication number
- CN111991013A CN111991013A CN202010916650.6A CN202010916650A CN111991013A CN 111991013 A CN111991013 A CN 111991013A CN 202010916650 A CN202010916650 A CN 202010916650A CN 111991013 A CN111991013 A CN 111991013A
- Authority
- CN
- China
- Prior art keywords
- detection
- skeletal muscle
- foot
- human body
- standing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/22—Ergometry; Measuring muscular strength or the force of a muscular blow
- A61B5/224—Measuring muscular strength
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
Abstract
The invention belongs to the technical field of detection, and particularly discloses a skeletal muscle strength and human body stability detection system and a detection method thereof. The invention solves the problems that the detection process of skeletal muscle strength and human body stability is complex, the efficiency is low, the cost is high, and the general public can not carry out autonomous detection in the prior art.
Description
Technical Field
The invention belongs to the technical field of detection, and particularly relates to a skeletal muscle strength and human body stability detection system and a detection method thereof.
Background
Sarcopenia (Sarcopenia), also known as Sarcopenia, was first proposed in 1989 by Irwin Rosenberg, professor tavus university of tavus, usa, and is considered to be "a decrease in skeletal muscle mass and a decline in its function with age". The European Sarcopenia Working Group (EWGSOP) defines it as a disease of progressive, decreased overall muscle mass and/or decreased muscle strength and/or decreased physiological function of muscles associated with aging, leading to a decreased functional status and quality of life in the elderly.
Skeletal muscle is the motive force of human motion system, and muscle aging and atrophy are important signs of human aging, and are very easy to cause problems such as fracture and joint injury. Sarcopenia refers to a syndrome resulting from a sustained loss of skeletal muscle mass and a decrease in strength and function. The old people with sarcopenia have the advantages of difficult standing, slow walking and easy falling and fracture, not only reduces the activity and the quality of life of the old people and increases the risks of falling and fracture, but also is a precondition and a condition for the occurrence and the development of chronic diseases such as diabetes, hypertension, coronary heart disease, respiratory failure and the like, and brings great influence and burden to the life, the society and the economy of people.
Muscle loss is one of the combined manifestations of aging in the human body, and sarcopenia is just muscle loss to a certain extent. In the compendium of health china 2030, the national health has been raised to the level of the national strategy. While "nourishing the aged", aging prevention should be more important to people. The common knowledge of the old first leg of the human body also laterally tells us that the aging of skeletal muscle is a signal of the old human body, so that the skeletal muscle strength and the stability of the human body are important bases for analyzing and diagnosing sarcopenia.
In the prior art, sarcopenia can be confirmed only by complex detection and diagnosis of professional doctors, the detection process of skeletal muscle strength and human body stability is complex, the efficiency is low, the cost is high, and general people cannot perform autonomous detection.
Disclosure of Invention
The present invention aims to solve at least one of the above technical problems to a certain extent.
Therefore, the present invention is directed to provide a skeletal muscle strength and human stability detection system and a detection method thereof, which are used to solve the problems of the prior art that the detection process of skeletal muscle strength and human stability is complicated, the efficiency is low, the cost is high, and general people cannot perform autonomous detection.
The technical scheme adopted by the invention is as follows:
a skeletal muscle force and human body stability detection system comprises a skeletal muscle force and human body stability detection unit, a data acquisition unit and a data storage and query unit, wherein the data acquisition unit is in communication connection with the skeletal muscle force and human body stability detection unit and the data storage and query unit respectively.
Further, skeletal muscle power and human stability detecting element includes the grip detection module, biped half indulges the detection module of standing, biped longitudinal row detection module, single-foot stand detection module, and sufficient detection module of standing, number of sitting times detection module and pace detection module are played in unit time, grip detection module, biped half indulges the detection module of standing, biped longitudinal row detection module, single-foot stand detection module, and sufficient detection module, number of sitting times detection module and pace detection module are all with data acquisition unit communication connection.
Furthermore, the grip strength detection module comprises an electronic grip strength meter and a grip strength detection controller, and the electronic grip strength meter, the grip strength detection controller and the data acquisition unit are sequentially in communication connection;
the double-foot semi-longitudinal standing detection module comprises a double-foot semi-longitudinal standing detection pressure sensor and a double-foot semi-longitudinal standing detection controller, and the double-foot semi-longitudinal standing detection pressure sensor, the double-foot semi-longitudinal standing detection controller and the data acquisition unit are sequentially in communication connection;
the double-foot longitudinal row standing detection module comprises a double-foot longitudinal row standing detection pressure sensor and a double-foot longitudinal row standing detection controller, and the double-foot longitudinal row standing detection pressure sensor, the double-foot longitudinal row standing detection controller and the data acquisition unit are sequentially in communication connection;
the single-foot standing detection module comprises a single-foot standing detection pressure sensor and a single-foot standing detection controller, and the single-foot standing detection pressure sensor, the single-foot standing detection controller and the data acquisition unit are sequentially in communication connection;
the foot merging standing detection module comprises a foot merging standing detection pressure sensor and a foot merging standing detection controller, and the foot merging standing detection pressure sensor, the foot merging standing detection controller and the data acquisition unit are sequentially in communication connection;
the unit time starting and sitting number detection module comprises a unit time starting and sitting number detection sensor and a unit time starting and sitting number detection controller, and the unit time starting and sitting number detection sensor, the unit time starting and sitting number detection controller and the data acquisition unit are sequentially in communication connection;
the pace detection module comprises a pace detection sensor and a pace detection controller, and the pace detection sensor, the pace detection controller and the data acquisition unit are sequentially in communication connection.
Furthermore, the data acquisition unit is a data acquisition server, the data acquisition server is provided with a printer and a communication module, the data acquisition server is respectively in communication connection with the communication module, the printer, the skeletal muscle strength and human body stability detection unit, and the communication module is in communication connection with the data storage query unit.
Furthermore, the data storage and query unit is a cloud server, the cloud server is in communication connection with the data acquisition unit, and the cloud server is in communication connection with a mobile query end and a PC query end.
A sarcopenia detection method based on a skeletal muscle strength and human body stability detection system comprises a skeletal muscle strength and human body stability detection unit, a data acquisition unit and a data storage and query unit, and the skeletal muscle strength and human body stability detection method comprises the following steps:
s1: the skeletal muscle force and human body stability detection unit acquires skeletal muscle force and human body stability data and sends the skeletal muscle force and human body stability data to the data acquisition unit;
s2: the data acquisition unit analyzes and processes the skeletal muscle force and human body stability data to obtain skeletal muscle force and human body stability detection results;
s3: storing the detection results of the skeletal muscle strength and the human body stability and the corresponding data of the skeletal muscle strength and the human body stability to a data storage and query unit;
s4: and acquiring skeletal muscle strength and human body stability reports by using a data storage and query unit.
Further, in step S1, the skeletal muscle strength and body stability data includes grip strength detection data, biped semi-longitudinal standing detection data, biped longitudinal row standing detection data, single-foot standing detection data, combined-foot standing detection data, number of sitting times per unit time detection data, and pace speed detection data.
Further, the specific step of step S2 is:
s2-1: the data acquisition unit scores skeletal muscle force and human body stability data according to scoring rules to obtain skeletal muscle force and human body stability scores of the current user;
s2-2: performing grouping analysis according to the skeletal muscle force and the human body stability score to obtain the skeletal muscle force and human body stability detection result of the current user;
s2-3: and storing the skeletal muscle force and the human body stability score to a data storage and query unit.
Further, in step S2-2, the formula of the skeletal muscle strength and the human stability test result is:
wherein, P is the skeletal muscle strength and the human stability score of the current user;
average values of skeletal muscle force and human body stability scores of the groups to which the current user belongs; ρ is the standard deviation of skeletal muscle strength and human stability score of the group to which the current user belongs.
Further, the formula of the standard deviation of skeletal muscle force and human stability score of the group to which the current user belongs is as follows:
in the formula, rho is the standard deviation of skeletal muscle force and human body stability fractions of the current group; piSkeletal muscle force and body stability scores for the ith user of the current group;
the skeletal muscle force and human body stability score average value of the current group is obtained; i is a user indication quantity; n is the total number of users currently grouped.
The invention has the beneficial effects that:
the skeletal muscle strength and human body stability detection system and the detection method thereof set the skeletal muscle strength and human body stability indexes and use related equipment to acquire and analyze the skeletal muscle strength and human body stability data, thereby realizing the autonomous detection and automatic analysis of the skeletal muscle strength and the human body stability, simplifying the detection process, improving the efficiency and reducing the detection cost.
Other advantageous effects of the present invention will be described in detail in the detailed description.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block diagram of a skeletal muscle strength and stability testing system;
FIG. 2 is a flow chart of a skeletal muscle strength and human stability testing method.
Detailed Description
The invention is further described with reference to the following figures and specific embodiments. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto. Functional details disclosed herein are merely illustrative of example embodiments of the invention. This invention may, however, be embodied in many alternate forms and should not be construed as limited to the embodiments set forth herein.
It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments of the invention. When the terms "comprises," "comprising," "includes," and/or "including" are used herein, they specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, numbers, steps, operations, elements, components, and/or groups thereof.
It should also be noted that, in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed substantially concurrently, or the figures may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
It should be understood that specific details are provided in the following description to facilitate a thorough understanding of example embodiments. However, it will be understood by those of ordinary skill in the art that the example embodiments may be practiced without these specific details. For example, systems may be shown in block diagrams in order not to obscure the examples in unnecessary detail. In other instances, well-known processes, structures and techniques may be shown without unnecessary detail in order to avoid obscuring example embodiments.
Example 1
As shown in fig. 1, the present embodiment provides a skeletal muscle strength and human stability detection system, which includes a skeletal muscle strength and human stability detection unit, a data acquisition unit, and a data storage and query unit, wherein the data acquisition unit is respectively in communication connection with the skeletal muscle strength and human stability detection unit and the data storage and query unit;
the skeletal muscle strength and human body stability detection unit is used for acquiring skeletal muscle strength and human body stability data of a user, the data acquisition unit is used for analyzing and processing the skeletal muscle strength and human body stability data to obtain a detection result of the skeletal muscle strength and the human body stability, the skeletal muscle strength and the human body stability data are acquired by setting skeletal muscle strength and human body stability indexes and using related equipment, the independent detection of the skeletal muscle strength and the human body stability is realized, the detection process is simplified, the efficiency is improved, the detection cost is reduced, the data storage and query unit is used for storing the skeletal muscle strength and human body stability data of the user and the detection result of the skeletal muscle strength and the human body stability, a query function of corresponding data and results is provided, and the practicability of the system is improved.
Preferably, the skeletal muscle strength and human body stability detection unit comprises a grip strength detection module, a biped semi-longitudinal standing detection module, a biped longitudinal row standing detection module, a single-foot standing detection module, a foot-merging standing detection module, a unit time sitting number detection module and a pace speed detection module, wherein the grip strength detection module, the biped semi-longitudinal standing detection module, the biped longitudinal row standing detection module, the single-foot standing detection module, the foot-merging standing detection module, the unit time sitting number detection module and the pace speed detection module are all in communication connection with the data acquisition unit.
Preferably, the grip strength detection module comprises an electronic grip strength meter and a grip strength detection controller, the electronic grip strength meter, the grip strength detection controller and the data acquisition unit are sequentially in communication connection, the electronic grip strength meter acquires grip strength detection data of a user, sends the grip strength detection data to the grip strength detection controller for processing, and finally sends the grip strength detection data to the data acquisition unit for analysis and scoring;
the biped semi-longitudinal standing detection module comprises a biped semi-longitudinal standing detection pressure sensor and a biped semi-longitudinal standing detection controller, the biped semi-longitudinal standing detection pressure sensor, the biped semi-longitudinal standing detection controller and a data acquisition unit are sequentially in communication connection, the biped semi-longitudinal standing detection pressure sensor is arranged at a preset semi-longitudinal standing position, the pressure data of the biped semi-longitudinal standing detection pressure sensor at the corresponding position is used for obtaining the time data of the semi-longitudinal standing posture, the time data are sent to the biped semi-longitudinal standing detection controller for processing, and finally the time data are sent to the data acquisition unit for analysis and scoring;
the double-foot longitudinal row standing detection module comprises a double-foot longitudinal row standing detection pressure sensor and a double-foot longitudinal row standing detection controller, the double-foot longitudinal row standing detection pressure sensor, the double-foot longitudinal row standing detection controller and a data acquisition unit are sequentially in communication connection, the double-foot longitudinal row standing detection pressure sensor is arranged at a preset position where the posture of the longitudinal row feet stands, the time data of the posture standing of the longitudinal row feet are obtained by detecting the pressure data of the double-foot longitudinal row standing detection pressure sensor at the corresponding position, the time data are sent to the double-foot longitudinal row standing detection controller for processing, and finally the time data are sent to the data acquisition unit for analysis and scoring;
the single-foot standing detection module comprises a single-foot standing detection pressure sensor and a single-foot standing detection controller, the single-foot standing detection pressure sensor, the single-foot standing detection controller and the data acquisition unit are sequentially in communication connection, the single-foot standing detection pressure sensor is arranged at a preset single-foot standing position, time data of single-foot standing is obtained by detecting pressure data of the single-foot standing detection pressure sensor at the corresponding position, the time data are sent to the single-foot standing detection controller for processing, and finally the time data are sent to the data acquisition unit for analysis and scoring;
the foot merging standing detection module comprises a foot merging standing detection pressure sensor and a foot merging standing detection controller, the foot merging standing detection pressure sensor, the foot merging standing detection controller and the data acquisition unit are sequentially in communication connection, the foot merging standing detection pressure sensor is arranged at a preset foot merging posture standing position, time data of the foot merging posture standing is obtained through pressure data of the foot merging standing detection pressure sensor at the corresponding position, the time data are sent to the foot merging standing detection controller to be processed, and finally the time data are sent to the data acquisition unit to be analyzed and scored;
the unit time sitting number detection module comprises a unit time sitting number detection sensor and a unit time sitting number detection controller, the unit time sitting number detection sensor, the unit time sitting number detection controller and the data acquisition unit are sequentially in communication connection, the unit time sitting number detection sensor is arranged at the top end of a seat of a user, the sitting number of the user is obtained by triggering the unit time sitting number detection sensor within a specified time, the sitting number is sent to the unit time sitting number detection controller for processing, and finally the sitting number is sent to the data acquisition unit for analysis and scoring;
the pace detection module comprises a pace detection sensor and a pace detection controller, the pace detection sensor, the pace detection controller and the data acquisition unit are sequentially in communication connection, the pace detection sensor is used for detecting time data used by a user for walking for a specified distance, the pace data of the user is obtained and sent to the pace detection controller for processing, and finally the pace detection sensor is sent to the data acquisition unit for analysis and scoring.
Preferably, the data acquisition unit is communicated with the skeletal muscle strength and human body stability detection unit through a bus, namely, the data acquisition unit is respectively communicated with the grip strength detection module, the biped semi-vertical standing detection module, the biped vertical row standing detection module, the single-foot standing detection module, the foot-combination standing detection module, the unit-time sitting number detection module and the pace speed detection module through the bus, and acquires various data of each module through the bus.
Preferably, the data acquisition unit is a data acquisition server, the data acquisition server is provided with a printer and a communication module, the data acquisition server is respectively in communication connection with the communication module, the printer and the skeletal muscle strength and human body stability detection unit, the communication module is in communication connection with the data storage and query unit, the data acquisition server receives skeletal muscle strength and human body stability data, analyzing and processing the skeletal muscle strength and human body stability data to obtain the detection results of the skeletal muscle strength and the human body stability, printing a corresponding report by using a printer, meanwhile, the skeletal muscle strength and human body stability detection result, the skeletal muscle strength and human body stability data are sent to the data storage and query unit through the communication module to be stored, the practicability is improved, and the skeletal muscle strength and human body stability detection result, the skeletal muscle strength and human body stability data are conveniently queried.
Preferably, the data storage and query unit is a cloud server, the cloud server is in communication connection with the data acquisition unit, the cloud server is in communication connection with a mobile query end and a PC query end, and a user can query the detection result of skeletal muscle strength and human stability and data of skeletal muscle strength and human stability through the mobile query end and the PC query end.
As shown in fig. 2, a sarcopenia detecting method based on a skeletal muscle strength and human stability detecting system, the skeletal muscle strength and human stability detecting system, includes a skeletal muscle strength and human stability detecting unit, a data collecting unit and a data storage and query unit, the skeletal muscle strength and human stability detecting method includes the following steps:
s1: the skeletal muscle force and human body stability detection unit acquires skeletal muscle force and human body stability data and sends the skeletal muscle force and human body stability data to the data acquisition unit;
the skeletal muscle strength and human body stability data comprise grip strength detection data, biped semi-longitudinal standing detection data, biped longitudinal row standing detection data, single-foot standing detection data, foot-merging standing detection data, unit time sitting number detection data and pace detection data;
s2: the data acquisition unit analyzes and processes the skeletal muscle strength and human body stability data to obtain a skeletal muscle strength and human body stability detection result, and the specific steps are as follows:
s2-1: the data acquisition unit scores skeletal muscle force and human body stability data according to scoring rules to obtain skeletal muscle force and human body stability scores of the current user;
s2-2: performing grouping analysis according to the skeletal muscle force and the human body stability score to obtain the skeletal muscle force and human body stability detection result of the current user;
grouping the users according to the comprehensive consideration of the age, the height, the weight and the sex of the current users;
the formula of the detection result of the skeletal muscle strength and the human body stability is as follows:
wherein, P is the skeletal muscle strength and the human stability score of the current user;
average values of skeletal muscle force and human body stability scores of the groups to which the current user belongs; rho is the standard deviation of skeletal muscle strength and human body stability scores of the groups to which the current user belongs;
the formula of the skeletal muscle force and human stability score standard deviation of the current user belonging group is as follows:
in the formula, rho is the standard deviation of skeletal muscle force and human body stability fractions of the current group; piSkeletal muscle force and body stability scores for the ith user of the current group;
the skeletal muscle force and human body stability score average value of the current group is obtained; i is a user indication quantity; n is the total number of users of the current grouping;
s2-3: storing the skeletal muscle strength and the human body stability score to a data storage and query unit;
s3: storing the detection results of the skeletal muscle strength and the human body stability and the corresponding data of the skeletal muscle strength and the human body stability to a data storage and query unit;
s4: and acquiring skeletal muscle strength and human body stability reports by using a data storage and query unit.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and they may alternatively be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, or fabricated separately as individual integrated circuit modules, or fabricated as a single integrated circuit module from multiple modules or steps. Thus, the present invention is not limited to any specific combination of hardware and software.
The embodiments described above are merely illustrative, and may or may not be physically separate, if referring to units illustrated as separate components; if reference is made to a component displayed as a unit, it may or may not be a physical unit, and may be located in one place or distributed over a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: modifications of the technical solutions described in the embodiments or equivalent replacements of some technical features may still be made. And such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
The present invention is not limited to the above-described alternative embodiments, and various other forms of products can be obtained by anyone in light of the present invention. The above detailed description should not be taken as limiting the scope of the invention, which is defined in the claims, and which the description is intended to be interpreted accordingly.
Claims (10)
1. A skeletal muscle strength and human stability detection system is characterized in that: the system comprises a skeletal muscle strength and human body stability detection unit, a data acquisition unit and a data storage and query unit, wherein the data acquisition unit is in communication connection with the skeletal muscle strength and human body stability detection unit and the data storage and query unit respectively.
2. The system for detecting skeletal muscle force and body stability of claim 1, wherein: skeletal muscle power and human stability detecting element includes that grip detection module, biped half indulge stand detection module, biped indulge row of standing detection module, single-foot stand detection module, and foot stand detection module, number of seats detection module and pace detection module, grip detection module, biped half indulge stand detection module, biped indulge row of standing detection module, single-foot stand detection module, and foot stand detection module, number of seats detection module and pace detection module all with data acquisition unit communication connection.
3. The skeletal muscle force and body stability testing system of claim 2, wherein: the grip strength detection module comprises an electronic grip strength meter and a grip strength detection controller, and the electronic grip strength meter, the grip strength detection controller and the data acquisition unit are sequentially in communication connection;
the double-foot semi-longitudinal standing detection module comprises a double-foot semi-longitudinal standing detection pressure sensor and a double-foot semi-longitudinal standing detection controller, and the double-foot semi-longitudinal standing detection pressure sensor, the double-foot semi-longitudinal standing detection controller and the data acquisition unit are sequentially in communication connection;
the double-foot longitudinal row standing detection module comprises a double-foot longitudinal row standing detection pressure sensor and a double-foot longitudinal row standing detection controller, and the double-foot longitudinal row standing detection pressure sensor, the double-foot longitudinal row standing detection controller and the data acquisition unit are sequentially in communication connection;
the single-foot standing detection module comprises a single-foot standing detection pressure sensor and a single-foot standing detection controller, and the single-foot standing detection pressure sensor, the single-foot standing detection controller and the data acquisition unit are sequentially in communication connection;
the foot merging standing detection module comprises a foot merging standing detection pressure sensor and a foot merging standing detection controller, and the foot merging standing detection pressure sensor, the foot merging standing detection controller and the data acquisition unit are sequentially in communication connection;
the unit time starting and sitting number detection module comprises a unit time starting and sitting number detection sensor and a unit time starting and sitting number detection controller, and the unit time starting and sitting number detection sensor, the unit time starting and sitting number detection controller and the data acquisition unit are sequentially in communication connection;
the pace detection module comprises a pace detection sensor and a pace detection controller, and the pace detection sensor, the pace detection controller and the data acquisition unit are sequentially in communication connection.
4. The system for detecting skeletal muscle force and body stability of claim 1, wherein: the data acquisition unit is data acquisition server, data acquisition server is provided with printer and communication module, data acquisition server respectively with communication module, printer and skeletal muscle power and human stability detecting element communication connection, communication module and data storage inquiry unit communication connection.
5. The system for detecting skeletal muscle force and body stability of claim 1, wherein: the data storage and query unit is a cloud server, the cloud server is in communication connection with the data acquisition unit, and the cloud server is in communication connection with a mobile query end and a PC query end.
6. A sarcopenia detecting method based on the skeletal muscle strength and human stability detecting system according to any one of claims 1 to 5, wherein the skeletal muscle strength and human stability detecting system comprises a skeletal muscle strength and human stability detecting unit, a data acquisition unit and a data storage and query unit, and the method comprises the following steps: the skeletal muscle strength and human body stability detection method comprises the following steps:
s1: the skeletal muscle force and human body stability detection unit acquires skeletal muscle force and human body stability data and sends the skeletal muscle force and human body stability data to the data acquisition unit;
s2: the data acquisition unit analyzes and processes the skeletal muscle force and human body stability data to obtain skeletal muscle force and human body stability detection results;
s3: storing the detection results of the skeletal muscle strength and the human body stability and the corresponding data of the skeletal muscle strength and the human body stability to a data storage and query unit;
s4: and acquiring skeletal muscle strength and human body stability reports by using a data storage and query unit.
7. The sarcopenia detection method according to claim 6, wherein: in step S1, the skeletal muscle strength and human body stability data includes grip strength detection data, biped semi-longitudinal standing detection data, biped longitudinal row standing detection data, single-foot standing detection data, foot-merging standing detection data, number of sitting times per unit time detection data, and pace speed detection data.
8. The sarcopenia detection method according to claim 6, wherein: the specific steps of step S2 are:
s2-1: the data acquisition unit scores skeletal muscle force and human body stability data according to scoring rules to obtain skeletal muscle force and human body stability scores of the current user;
s2-2: performing grouping analysis according to the skeletal muscle force and the human body stability score to obtain the skeletal muscle force and human body stability detection result of the current user;
s2-3: and storing the skeletal muscle force and the human body stability score to a data storage and query unit.
9. The sarcopenia detection method according to claim 6, wherein: in step S2-2, the formula of the detection result of skeletal muscle strength and human stability is:
wherein, P is the skeletal muscle strength and the human stability score of the current user;
average values of skeletal muscle force and human body stability scores of the groups to which the current user belongs; ρ is the standard deviation of skeletal muscle strength and human stability score of the group to which the current user belongs.
10. The sarcopenia detection method according to claim 9, wherein: the formula of the skeletal muscle strength and human body stability score standard deviation of the group to which the current user belongs is as follows:
in the formula, rho is the standard deviation of skeletal muscle force and human body stability fractions of the current group; piSkeletal muscle force and body stability scores for the ith user of the current group;
the skeletal muscle force and human body stability score average value of the current group is obtained; i is a user indication quantity; n is the total number of users currently grouped.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010916650.6A CN111991013A (en) | 2020-09-03 | 2020-09-03 | Skeletal muscle strength and human body stability detection system and detection method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010916650.6A CN111991013A (en) | 2020-09-03 | 2020-09-03 | Skeletal muscle strength and human body stability detection system and detection method thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111991013A true CN111991013A (en) | 2020-11-27 |
Family
ID=73465364
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010916650.6A Pending CN111991013A (en) | 2020-09-03 | 2020-09-03 | Skeletal muscle strength and human body stability detection system and detection method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111991013A (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1723847A (en) * | 2004-07-21 | 2006-01-25 | 松下电工株式会社 | Physical activity measuring system |
| CN106618487A (en) * | 2016-10-31 | 2017-05-10 | 北京城市系统工程研究中心 | Method for evaluating balance capacity of old people |
| CN106805980A (en) * | 2017-01-24 | 2017-06-09 | 重庆小爱科技有限公司 | A kind of gait analysis system and analysis method |
| WO2018173036A1 (en) * | 2017-03-22 | 2018-09-27 | Selfit Medical Ltd | Systems and methods for physical therapy using augmented reality and treatment data collection and analysis |
| CN109480856A (en) * | 2018-12-29 | 2019-03-19 | 中国科学院合肥物质科学研究院 | Human body static balancing capability comparison system and method based on multistation appearance |
| CN109674478A (en) * | 2018-12-25 | 2019-04-26 | 沈阳体育学院 | A kind of total balance of the body quality test instrument for training |
| CN111481199A (en) * | 2020-03-23 | 2020-08-04 | 华为技术有限公司 | Method for detecting human muscle health degree and electronic equipment |
-
2020
- 2020-09-03 CN CN202010916650.6A patent/CN111991013A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1723847A (en) * | 2004-07-21 | 2006-01-25 | 松下电工株式会社 | Physical activity measuring system |
| CN106618487A (en) * | 2016-10-31 | 2017-05-10 | 北京城市系统工程研究中心 | Method for evaluating balance capacity of old people |
| CN106805980A (en) * | 2017-01-24 | 2017-06-09 | 重庆小爱科技有限公司 | A kind of gait analysis system and analysis method |
| WO2018173036A1 (en) * | 2017-03-22 | 2018-09-27 | Selfit Medical Ltd | Systems and methods for physical therapy using augmented reality and treatment data collection and analysis |
| CN109674478A (en) * | 2018-12-25 | 2019-04-26 | 沈阳体育学院 | A kind of total balance of the body quality test instrument for training |
| CN109480856A (en) * | 2018-12-29 | 2019-03-19 | 中国科学院合肥物质科学研究院 | Human body static balancing capability comparison system and method based on multistation appearance |
| CN111481199A (en) * | 2020-03-23 | 2020-08-04 | 华为技术有限公司 | Method for detecting human muscle health degree and electronic equipment |
Non-Patent Citations (1)
| Title |
|---|
| 山东师范学院: "《生理卫生》", 30 June 1977 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Corbin et al. | Are American children and youth fit? | |
| Weiss et al. | An instrumented timed up and go: the added value of an accelerometer for identifying fall risk in idiopathic fallers | |
| CN105455976B (en) | Intelligent rehabilitation wheelchair | |
| US6920348B2 (en) | Method and apparatus for determining metabolic factors from an electrocardiogram | |
| Wang et al. | Links between the mechanics of ventilation and spine stability | |
| Ambegaonkar et al. | Upper-body muscular endurance in female university-level modern dancers: a pilot study | |
| Jee et al. | Development and application of biological age prediction models with physical fitness and physiological components in Korean adults | |
| Patterson et al. | Comparison of a mobile technology application with the balance error scoring system | |
| Fardy et al. | Benefits of arm exercise in cardiac rehabilitation | |
| Chapman et al. | Perceptual, mechanical, and electromyographic responses to different relative loads in the parallel squat | |
| JP2011115362A (en) | Cognitive function evaluation system | |
| CN1275179C (en) | Computer evaluating method for human body sub-health status | |
| Narayanan et al. | A wearable triaxial accelerometry system for longitudinal assessment of falls risk | |
| WO2019010161A1 (en) | Systems, devices, and methods for acquiring, validating and analyzing athletic movement data | |
| EP3012755B1 (en) | Muscle condition change determination apparatus and program | |
| Borysenko et al. | Influence of body length on orthostatic test parameters of student-athletes | |
| CN111991013A (en) | Skeletal muscle strength and human body stability detection system and detection method thereof | |
| Montes et al. | Fitbit Flex: energy expenditure and step count evaluation | |
| Puranik et al. | Wearable device for yogic breathing | |
| Chauhan et al. | Impact of physical training on aerobic capacity on under-graduate students | |
| Bozic et al. | Evaluation of novel tests of neuromuscular function based on brief muscle actions | |
| CN104107040A (en) | Breathing analyzing and display system and method | |
| Morgulec et al. | Anaerobic performance of active and sedentary male individuals with quadriplegia | |
| da Silva et al. | Time Under Tension, Muscular Activation, and Blood Lactate Responses to Perform 8, 10, and 12RM in the Bench Press Exercise. | |
| Smith et al. | Upper-body exercise |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20201127 |
|
| RJ01 | Rejection of invention patent application after publication |